Tamburini_AVIDseq
d2_DC
Cell type markers
# Cell type colors
cell_types <- sobj@meta.data %>%
pull(!!sym(cell_type_id)) %>%
unique()
names(cell_types) <- cell_types
type_cols <- theme_cols
names(type_cols) <- cell_types
type_cols <- type_cols[!is.na(names(type_cols))]
# # Find all cell type markers
# Idents(sobj) <- sobj %>%
# FetchData(cell_type_id)
#
# all_type_marks <- sobj %>%
# FindAllMarkers(only.pos = T) %>%
# as_tibble() %>%
# filter(p_val_adj < 0.05)
#
# # Cell type UMAP
# type_umap <- sobj %>%
# plot_features(
# feature = cell_type_id,
# plot_cols = type_cols,
# feat_levels = names(type_cols)
# ) +
# guides(color = col_guide) +
# blank_theme +
# theme(
# legend.position = "top",
# legend.title = element_blank(),
# legend.text = element_text(size = 10)
# )
#
# # Marker plots
# for (i in seq_along(type_cols)) {
# cat("\n#### ", names(type_cols[i]), "\n", sep = "")
#
# type_marks <- all_type_marks %>%
# filter(cluster == names(type_cols[i]))
#
# type_marks_fig <- sobj %>%
# create_marker_fig(
# input_markers = type_marks,
# type_id = cell_type_id,
# input_umap = type_umap,
# umap_color = type_cols[[i]],
# box_colors = type_cols
# )
#
# # type_marks %>%
# # kable() %>%
# # kable_styling(fixed_thead = T) %>%
# # print()
#
# print(type_marks_fig)
# cat("\n\n---\n\n<br>\n\n<br>\n\n")
# }Cell cluster markers
# Cell type colors
cell_clusts <- sobj@meta.data %>%
mutate(
type_clust = str_extract(!!sym(cluster_id), "^[0-9]+"),
type_clust = as.numeric(type_clust)
) %>%
arrange(!!sym(cell_type_id), type_clust) %>%
pull(!!sym(cluster_id)) %>%
unique()
names(cell_clusts) <- cell_clusts
clust_cols <- theme_cols
names(clust_cols) <- cell_clusts
clust_cols <- clust_cols[!is.na(names(clust_cols))]
# # Find all cell cluster markers
# Idents(sobj) <- sobj %>%
# FetchData(cluster_id)
#
# all_clust_marks <- sobj %>%
# FindAllMarkers(only.pos = T) %>%
# as_tibble() %>%
# filter(p_val_adj < 0.05)
#
# # Cluster UMAP
# clust_umap <- sobj %>%
# plot_features(
# feature = cluster_id,
# plot_cols = clust_cols,
# feat_levels = names(clust_cols)
# ) +
# guides(color = col_guide) +
# blank_theme +
# theme(
# legend.position = "top",
# legend.title = element_blank(),
# legend.text = element_text(size = 10)
# )
#
# # Cluster plots
# for (i in seq_along(clust_cols)) {
# cat("\n#### ", names(clust_cols[i]), "\n", sep = "")
#
# clust_marks <- all_clust_marks %>%
# filter(cluster == names(clust_cols[i]))
#
# clust_marks_fig <- sobj %>%
# create_marker_fig(
# input_markers = clust_marks,
# type_id = cluster_id,
# input_umap = clust_umap,
# umap_color = clust_cols[[i]],
# box_colors = clust_cols
# )
#
# print(clust_marks_fig)
# cat("\n\n---\n\n<br>\n\n<br>\n\n")
# }Separate cell cluster markers
# Find cluster markers separately for each cell type
sep_clust_marks <- cell_types %>%
map(find_sep_clust_markers, sobj) %>%
compact() %>%
bind_rows()
sep_clusts <- sep_clust_marks$cluster %>%
unique()
sep_clusts <- clust_cols[names(clust_cols) %in% sep_clusts] %>%
names()
# Cluster plots
for (i in seq_along(sep_clusts)) {
cat("\n#### ", sep_clusts[i], "\n", sep = "")
sep_marks <- sep_clust_marks %>%
filter(cluster == sep_clusts[i])
type <- sep_clusts[i] %>%
str_remove("^[0-9]+-")
sep_cols <- clust_cols[grepl(str_c("-", type), names(clust_cols))]
sep_cols <- c( "Other" = "#f0f0f0", sep_cols)
sep_clust_umap <- sobj %>%
FetchData(c("UMAP_1", "UMAP_2", cell_type_id, cluster_id)) %>%
as_tibble(rownames = "cell_id") %>%
mutate(!!sym(cluster_id) := if_else(!!sym(cell_type_id) != type, "Other", !!sym(cluster_id))) %>%
plot_features(
feature = cluster_id,
plot_cols = sep_cols,
feat_levels = names(sep_cols)
) +
guides(color = col_guide) +
blank_theme +
theme(
legend.position = "top",
legend.title = element_blank(),
legend.text = element_text(size = 10)
)
sep_clust_marks_fig <- sobj %>%
create_marker_fig(
input_markers = sep_marks,
type_id = cluster_id,
input_umap = sep_clust_umap,
umap_color = sep_cols[sep_clusts[i]],
box_colors = sep_cols,
cell_type = type
)
print(sep_clust_marks_fig)
cat("\n\n---\n\n<br>\n\n<br>\n\n")
}0-CCR7hi mig cDC2
6-CCR7hi mig cDC2
7-CCR7hi mig cDC2
12-CCR7hi mig cDC2
9-cDC1
14-cDC1
16-cDC1
1-cDC2 Tbet-
2-cDC2 Tbet-
4-cDC2 Tbet-
8-cDC2 Tbet-
10-cDC2 Tbet-
13-cDC2 Tbet-
15-cDC2 Tbet-
d14_DC
Cell type markers
# Cell type colors
cell_types <- sobj@meta.data %>%
pull(!!sym(cell_type_id)) %>%
unique()
names(cell_types) <- cell_types
type_cols <- theme_cols
names(type_cols) <- cell_types
type_cols <- type_cols[!is.na(names(type_cols))]
# # Find all cell type markers
# Idents(sobj) <- sobj %>%
# FetchData(cell_type_id)
#
# all_type_marks <- sobj %>%
# FindAllMarkers(only.pos = T) %>%
# as_tibble() %>%
# filter(p_val_adj < 0.05)
#
# # Cell type UMAP
# type_umap <- sobj %>%
# plot_features(
# feature = cell_type_id,
# plot_cols = type_cols,
# feat_levels = names(type_cols)
# ) +
# guides(color = col_guide) +
# blank_theme +
# theme(
# legend.position = "top",
# legend.title = element_blank(),
# legend.text = element_text(size = 10)
# )
#
# # Marker plots
# for (i in seq_along(type_cols)) {
# cat("\n#### ", names(type_cols[i]), "\n", sep = "")
#
# type_marks <- all_type_marks %>%
# filter(cluster == names(type_cols[i]))
#
# type_marks_fig <- sobj %>%
# create_marker_fig(
# input_markers = type_marks,
# type_id = cell_type_id,
# input_umap = type_umap,
# umap_color = type_cols[[i]],
# box_colors = type_cols
# )
#
# # type_marks %>%
# # kable() %>%
# # kable_styling(fixed_thead = T) %>%
# # print()
#
# print(type_marks_fig)
# cat("\n\n---\n\n<br>\n\n<br>\n\n")
# }Cell cluster markers
# Cell type colors
cell_clusts <- sobj@meta.data %>%
mutate(
type_clust = str_extract(!!sym(cluster_id), "^[0-9]+"),
type_clust = as.numeric(type_clust)
) %>%
arrange(!!sym(cell_type_id), type_clust) %>%
pull(!!sym(cluster_id)) %>%
unique()
names(cell_clusts) <- cell_clusts
clust_cols <- theme_cols
names(clust_cols) <- cell_clusts
clust_cols <- clust_cols[!is.na(names(clust_cols))]
# # Find all cell cluster markers
# Idents(sobj) <- sobj %>%
# FetchData(cluster_id)
#
# all_clust_marks <- sobj %>%
# FindAllMarkers(only.pos = T) %>%
# as_tibble() %>%
# filter(p_val_adj < 0.05)
#
# # Cluster UMAP
# clust_umap <- sobj %>%
# plot_features(
# feature = cluster_id,
# plot_cols = clust_cols,
# feat_levels = names(clust_cols)
# ) +
# guides(color = col_guide) +
# blank_theme +
# theme(
# legend.position = "top",
# legend.title = element_blank(),
# legend.text = element_text(size = 10)
# )
#
# # Cluster plots
# for (i in seq_along(clust_cols)) {
# cat("\n#### ", names(clust_cols[i]), "\n", sep = "")
#
# clust_marks <- all_clust_marks %>%
# filter(cluster == names(clust_cols[i]))
#
# clust_marks_fig <- sobj %>%
# create_marker_fig(
# input_markers = clust_marks,
# type_id = cluster_id,
# input_umap = clust_umap,
# umap_color = clust_cols[[i]],
# box_colors = clust_cols
# )
#
# print(clust_marks_fig)
# cat("\n\n---\n\n<br>\n\n<br>\n\n")
# }Separate cell cluster markers
# Find cluster markers separately for each cell type
sep_clust_marks <- cell_types %>%
map(find_sep_clust_markers, sobj) %>%
compact() %>%
bind_rows()
sep_clusts <- sep_clust_marks$cluster %>%
unique()
sep_clusts <- clust_cols[names(clust_cols) %in% sep_clusts] %>%
names()
# Cluster plots
for (i in seq_along(sep_clusts)) {
cat("\n#### ", sep_clusts[i], "\n", sep = "")
sep_marks <- sep_clust_marks %>%
filter(cluster == sep_clusts[i])
type <- sep_clusts[i] %>%
str_remove("^[0-9]+-")
sep_cols <- clust_cols[grepl(str_c("-", type), names(clust_cols))]
sep_cols <- c( "Other" = "#f0f0f0", sep_cols)
sep_clust_umap <- sobj %>%
FetchData(c("UMAP_1", "UMAP_2", cell_type_id, cluster_id)) %>%
as_tibble(rownames = "cell_id") %>%
mutate(!!sym(cluster_id) := if_else(!!sym(cell_type_id) != type, "Other", !!sym(cluster_id))) %>%
plot_features(
feature = cluster_id,
plot_cols = sep_cols,
feat_levels = names(sep_cols)
) +
guides(color = col_guide) +
blank_theme +
theme(
legend.position = "top",
legend.title = element_blank(),
legend.text = element_text(size = 10)
)
sep_clust_marks_fig <- sobj %>%
create_marker_fig(
input_markers = sep_marks,
type_id = cluster_id,
input_umap = sep_clust_umap,
umap_color = sep_cols[sep_clusts[i]],
box_colors = sep_cols,
cell_type = type
)
print(sep_clust_marks_fig)
cat("\n\n---\n\n<br>\n\n<br>\n\n")
}3-CCR7hi mig cDC2
6-CCR7hi mig cDC2
11-CCR7hi mig cDC2
2-cDC1
8-cDC1
12-cDC1
0-cDC2 Tbet-
1-cDC2 Tbet-
4-cDC2 Tbet-
7-cDC2 Tbet-
14-cDC2 Tbet-
17-cDC2 Tbet-
